
import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


__lowerCAmelCase     :	Tuple       			=  '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.\n\nIn March 2021, Hugging Face raised $40 million in a Series B funding round.[3]\n\nOn April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]\n'




class 			UpperCAmelCase_     (					unittest.TestCase    ,			_A	):


  '''simple docstring'''







  def 				_lowercase				(					self     :					Tuple       )     ->      str:







    """simple docstring"""






    __magic_name__								=			load_tool("""text-question-answering"""       )
    self.tool.setup()
    __magic_name__								=			load_tool("""text-question-answering"""     ,				remote=UpperCamelCase__       )
  def 				_lowercase				(					self     :					Optional[Any]       )     ->      Any:







    """simple docstring"""






    __magic_name__								=			self.tool(UpperCamelCase__     ,				"""What did Hugging Face do in April 2021?"""       )
    self.assertEqual(UpperCamelCase__     ,				"""launched the BigScience Research Workshop"""       )
  def 				_lowercase				(					self     :					str       )     ->      List[Any]:







    """simple docstring"""






    __magic_name__								=			self.remote_tool(UpperCamelCase__     ,				"""What did Hugging Face do in April 2021?"""       )
    self.assertEqual(UpperCamelCase__     ,				"""launched the BigScience Research Workshop"""       )
  def 				_lowercase				(					self     :					Tuple       )     ->      List[Any]:







    """simple docstring"""






    __magic_name__								=			self.tool(text=UpperCamelCase__     ,				question="""What did Hugging Face do in April 2021?"""       )
    self.assertEqual(UpperCamelCase__     ,				"""launched the BigScience Research Workshop"""       )





  def 				_lowercase				(					self     :					List[Any]       )     ->      List[str]:







    """simple docstring"""






    __magic_name__								=			self.remote_tool(text=UpperCamelCase__     ,				question="""What did Hugging Face do in April 2021?"""       )
    self.assertEqual(UpperCamelCase__     ,				"""launched the BigScience Research Workshop"""       )



# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCAmelCase     :	Tuple       			=  {'configuration_timm_backbone': ['TimmBackboneConfig']}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCAmelCase     :	str       			=  ['TimmBackbone']


if TYPE_CHECKING:
    from .configuration_timm_backbone import TimmBackboneConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_timm_backbone import TimmBackbone

else:
    import sys

    __lowerCAmelCase     :	str       			=  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

